About lab
Boltz Workflow: Tuberculosis Target
Tuberculosis Target Workflow is a curated BioSimulant Boltz workflow. It runs a single curated target sequence and a single reference ligand SMILES through Boltz-2, then presents the predicted complex, binder probability, affinity-like value, confidence metrics, run metadata, and report-ready caveats in the standard Biosimulant lab interface.
The workflow is designed for learning, comparison against known examples, and early biological hypothesis generation. It is not experimental validation, a clinical prediction, or a replacement for docking review, MD/FEP, assay design, or wet-lab confirmation.
Workflow Status
This lab validates locally, exports as a portable .bsilab package, and has a successful private pre-publication GPU-backed run. It is published on Biosimulant Hub and now uses a multi-stage Compose graph. The graph separates source-backed context, input assembly, Boltz-2 prediction, conservative interpretation, and visual reporting.
Publication checklist:
- manifest validation passes: complete
- strict package export passes: complete
- entrypoints import successfully: complete
- unit tests pass: complete
- at least one real GPU run completes: complete
- run results include structure, affinity, confidence, metadata, and visuals: complete
- screenshots/assets are captured from the real run: complete
- Hub workflow card is public and points at the published lab id: complete
Pre-Publication Run Evidence
The current assets and metrics are derived from this private staged remote run:
- run id:
4e2b6781-22fb-4c23-87ed-2371c468f24c - staged lab id:
d7f38fb4-7fd2-43b8-9cdf-a1394daff930 - run lab commit:
38f64781f66d965bd0618324ea2b7e4dee1fa5b7893e80c42d16a902122707b4 - remote size: GPU A10G
- status: completed
- duration: 533.3 seconds
- credits settled: 45
Key outputs from the run:
affinity_probability_binary:0.49277544021606445affinity_pred_value:0.9798953533172609confidence_score:0.9177390933036804complex_plddt:0.9237298369407654iptm:0.8937761783599854ligand_iptm:0.8937761783599854
Curated Known Example
The bundled known-example mode starts with:
- target: Mycobacterium tuberculosis InhA enoyl-ACP reductase
- target source: RCSB PDB
3FNEsequence FASTA - ligand: Triclosan reference inhibitor-like ligand
- ligand source: PubChem CID
5564 - protein sequence length: 269 amino acids
- MSA server usage enabled for the default example
The workflow is not a tuberculosis treatment recommendation and does not replace microbiology, resistance, or assay evidence.
What This Workflow Does
When run, the workflow:
- Builds a Boltz-2 request from the curated or user-supplied protein and ligand inputs.
- Runs the Boltz-2 CLI on a GPU-backed runtime.
- Parses the top-ranked structure artifact.
- Parses Boltz-2 affinity and confidence summaries.
- Emits Biosimulant visuals and report-ready outputs.
Compose Workflow Graph
The published workflow is intentionally split into real BioSimulant modules:
tuberculosis_target_contextemits source-backed target, ligand, disease/use-case, provenance, and caveat context.inha_ligand_setupresolves the public protein, ligand, MSA, and run-option inputs into the exact Boltz request.boltz_boltz2_affinity_predictorruns the unchanged Boltz-2 scientific wrapper.tb_prediction_interpreterconverts raw Boltz outputs into conservative evidence fields without adding new biological claims.visualisationrenders the 3D structure, confidence/affinity summaries, source context, request traceability, and Q/A caveat cards.
This makes the Compose view match the workflow promise while keeping Boltz-2 as the only predictive scientific model. The surrounding modules are provenance, request assembly, interpretation, and presentation stages.
Inputs
protein_sequence: amino-acid sequence for the target protein. If omitted, the bundled known example is used.ligand_smiles: SMILES string for the ligand. If omitted, the bundled known example ligand is used.msa_path: optional path to a precomputed.a3mMSA file.run_options: optional record for workflow/runtime options.
The known example mode works because lab.yaml defines defaults directly on the Boltz runner model. A new user can click Run without knowing YAML, SMILES formatting details, or Boltz CLI arguments.
Outputs
structure_artifacts: paths to the predicted complex structure files, usually mmCIF.affinity_summary: affinity-style outputs parsed from Boltz-2.confidence_summary: model confidence outputs for the top-ranked prediction.run_metadata: execution metadata, output paths, captured logs, and status.
The visualisation model turns these records into standard Biosimulant run visuals, including a structure viewer and summary metrics.
Reading The Affinity Outputs
Boltz-2 distinguishes two affinity-oriented outputs that should not be collapsed into one meaning.
affinity_probability_binary is most useful as a binder-vs-decoy style signal. In product language, it is the binder probability. It is useful when comparing likely binders against unlikely binders under a hit-discovery framing.
affinity_pred_value is intended for ligand-optimization style use cases. In product language, it is an affinity-like value. It should be used cautiously and comparatively, not as a direct experimental measurement.
Both outputs are model predictions. They can help rank hypotheses for follow-up, but they do not prove binding, potency, selectivity, mechanism, or biological effect.
Reading The Structure
The structure viewer shows the predicted protein-ligand complex from the top-ranked Boltz output. Use it as a sanity check:
- Is the ligand near a plausible pocket?
- Is the interface confidence reasonable?
- Does the pose look inconsistent with the score?
- Are there warnings in run metadata?
A high binder probability with an implausible pose should be treated as suspicious. A plausible pose with weak confidence should also be treated as uncertain.
Safe Use Cases
This workflow is best for infectious-disease target context, known inhibitor-like examples, and reportable early screening hypotheses.
Safe uses include:
- Learn protein-ligand modeling workflows.
- Compare known ligand examples.
- Generate early hypotheses.
- Prepare candidate lists for deeper review.
- Create reproducible computational biology reports.
- Teach structure-based drug-discovery concepts.
Do Not Claim
- Validated drug discovery.
- Clinical prediction.
- Medical diagnosis.
- Final compound selection.
- Wet-lab replacement.
- FEP replacement.
- Experimentally guaranteed binding-affinity certainty.
Assets
The current screenshots were captured from the successful private pre-publication GPU run above, using its persisted mmCIF structure artifact and parsed run metrics.


Implementation Notes
This workflow intentionally reuses the existing Boltz-2 affinity predictor and visualisation modules. The product difference is in the lab packaging:
- guided disease or target context
- workflow tags
- known example defaults
- safe input names
- report-oriented caveats
- future Hub placement in the Boltz Workflows section
Guided Boltz-2 workflow for exploring a Mycobacterium tuberculosis InhA target with a triclosan reference ligand example, binder probability, affinity-like value, confidence metrics, and reproducible report context.
Runtime
Runs
Metadata
Manifest
{
"io": {
"inputs": [
{
"name": "protein_sequence",
"label": "InhA Target Sequence",
"maps_to": "inha_ligand_setup.protein_sequence",
"description": "Amino-acid sequence for the curated Mycobacterium tuberculosis InhA target; maps directly to the Boltz-2 protein input."
},
{
"name": "ligand_smiles",
"label": "Triclosan Ligand SMILES",
"maps_to": "inha_ligand_setup.ligand_smiles",
"description": "SMILES string for the triclosan reference inhibitor-like ligand example; maps directly to the Boltz-2 ligand input."
},
{
"name": "msa_path",
"label": "Precomputed MSA Path",
"maps_to": "inha_ligand_setup.msa_path",
"description": "Optional path to a precomputed MSA file; leave unset when the configured Boltz MSA server is used."
},
{
"name": "run_options",
"label": "Boltz Run Options",
"maps_to": "inha_ligand_setup.run_options",
"description": "Optional structured controls for the Boltz workflow, including source metadata, sampling settings, and interpretation scope."
}
],
"outputs": [
{
"name": "scenario_context",
"label": "Workflow Scenario Context",
"maps_to": "tuberculosis_target_context.scenario_context",
"description": "Source-backed target, ligand, use-case, provenance, and caveat context for this Boltz workflow."
},
{
"name": "assembled_boltz_request",
"label": "Assembled Boltz Request",
"maps_to": "inha_ligand_setup.assembled_boltz_request",
"description": "Traceable summary of the protein, ligand, MSA, and run options prepared for Boltz."
},
{
"name": "affinity_summary",
"label": "Affinity-Style Summary",
"maps_to": "boltz_boltz2_affinity_predictor.affinity_summary",
"description": "Parsed Boltz-2 binder probability and affinity-like outputs for this InhA-ligand prediction."
},
{
"name": "confidence_summary",
"label": "Structure Confidence Summary",
"maps_to": "boltz_boltz2_affinity_predictor.confidence_summary",
"description": "Parsed Boltz-2 confidence outputs for the predicted InhA-ligand complex."
},
{
"name": "structure_artifacts",
"label": "Predicted Complex Structure Artifacts",
"maps_to": "boltz_boltz2_affinity_predictor.structure_artifacts",
"description": "File-backed predicted complex structures used by the 3D visualisation."
},
{
"name": "run_metadata",
"label": "Boltz Run Metadata",
"maps_to": "boltz_boltz2_affinity_predictor.run_metadata",
"description": "Runtime status, command metadata, logs, and caveats for the latest Boltz invocation."
},
{
"name": "prediction_evidence",
"label": "Conservative Prediction Evidence",
"maps_to": "tb_prediction_interpreter.prediction_evidence",
"description": "Interpreted Boltz output evidence with request traceability and explicit scientific caveats."
}
]
},
"tags": [
"boltz-workflow",
"boltz",
"protein-ligand",
"affinity",
"structural-biology",
"guided-workflow",
"gpu",
"tuberculosis",
"infectious-disease",
"inha"
],
"title": "Boltz Workflow: Tuberculosis Target",
"models": [
{
"path": "owned/models/tuberculosis_target_context",
"alias": "tuberculosis_target_context",
"parameters": {
"scenario": {
"caveat": "Boltz-2 outputs are computational structure and affinity-style predictions for hypothesis generation; they are not experimental binding, potency, selectivity, clinical, or efficacy evidence.",
"source_pdb": "3FNE",
"ligand_name": "Triclosan reference inhibitor-like ligand",
"ligand_role": "reference inhibitor-like ligand",
"target_name": "Mycobacterium tuberculosis InhA enoyl-ACP reductase",
"disease_area": "tuberculosis target exploration",
"target_family": "InhA enoyl-ACP reductase",
"workflow_name": "Tuberculosis Target Workflow",
"workflow_context": "Guided Boltz-2 known-example workflow for Mycobacterium tuberculosis InhA enoyl-ACP reductase and Triclosan reference inhibitor-like ligand",
"workflow_question": "What does Boltz-2 predict for this tuberculosis target and reference ligand?",
"source_pubchem_cid": "5564",
"interpretation_scope": "Learning and early hypothesis generation only",
"protein_sequence_length": 269
},
"integration_step": 0.01
},
"provenance": {
"owned_path": "owned/models/tuberculosis_target_context"
}
},
{
"path": "owned/models/inha_ligand_setup",
"alias": "inha_ligand_setup",
"parameters": {
"workflow_kind": "single",
"workflow_name": "Tuberculosis Target Workflow",
"integration_step": 0.01,
"default_run_options": {
"source_pdb": "3FNE",
"ligand_name": "Triclosan reference inhibitor-like ligand",
"target_name": "Mycobacterium tuberculosis InhA enoyl-ACP reductase",
"workflow_name": "Tuberculosis Target Workflow",
"workflow_context": "Guided Boltz-2 known-example workflow for Mycobacterium tuberculosis InhA enoyl-ACP reductase and Triclosan reference inhibitor-like ligand",
"source_pubchem_cid": "5564",
"interpretation_scope": "Learning and early hypothesis generation only"
},
"default_ligand_smiles": "C1=CC(=C(C=C1Cl)O)OC2=C(C=C(C=C2)Cl)Cl",
"default_protein_sequence": "MTGLLDGKRILVSGIITDSSIAFHIARVAQEQGAQLVLTGFDRLRLIQRITDRLPAKAPLLELDVQNEEHLASLAGRVTEAIGAGNKLDGVVHSIGFMPQTGMGINPFFDAPYADVSKGIHISAYSYASMAKALLPIMNPGGSIVGMDFDPSRAMPAYNWMTVAKSALESVNRFVAREAGKYGVRSNLVAAGPIRTLAMSAIVGGALGEEAGAQIQLLEEGWDQRAPIGWNMKDATPVAKTVCALLSDWLPATTGDIIYADGGAHTQLL"
},
"provenance": {
"owned_path": "owned/models/inha_ligand_setup"
}
},
{
"path": "owned/models/boltz_boltz2_affinity_predictor",
"alias": "boltz_boltz2_affinity_predictor",
"parameters": {
"override": true,
"accelerator": "gpu",
"runtime_mode": "managed",
"output_format": "mmcif",
"sampling_steps": 200,
"use_msa_server": true,
"recycling_steps": 3,
"diffusion_samples": 1
},
"provenance": {
"owned_path": "owned/models/boltz_boltz2_affinity_predictor"
}
},
{
"path": "owned/models/tb_prediction_interpreter",
"alias": "tb_prediction_interpreter",
"parameters": {
"mode": "single",
"caveat": "Boltz-2 outputs are computational structure and affinity-style predictions for hypothesis generation; they are not experimental binding, potency, selectivity, clinical, or efficacy evidence.",
"core_alias": "boltz_boltz2_affinity_predictor",
"workflow_name": "Tuberculosis Target Workflow",
"integration_step": 0.01
},
"provenance": {
"owned_path": "owned/models/tb_prediction_interpreter"
}
},
{
"path": "owned/models/visualisation",
"alias": "visualisation",
"parameters": {
"mode": "boltz",
"lab_title": "Boltz Workflow: Tuberculosis Target",
"source_alias": "boltz_boltz2_affinity_predictor",
"context_alias": "tuberculosis_target_context",
"assembler_alias": "inha_ligand_setup",
"integration_step": 0.01,
"interpreter_alias": "tb_prediction_interpreter"
},
"provenance": {
"owned_path": "owned/models/visualisation"
}
}
],
"wiring": [
{
"to": [
"inha_ligand_setup.scenario_context",
"tb_prediction_interpreter.scenario_context",
"visualisation.tuberculosis_target_context_scenario_context"
],
"from": "tuberculosis_target_context.scenario_context"
},
{
"to": [
"boltz_boltz2_affinity_predictor.protein_sequence"
],
"from": "inha_ligand_setup.protein_sequence"
},
{
"to": [
"boltz_boltz2_affinity_predictor.ligand_smiles"
],
"from": "inha_ligand_setup.ligand_smiles"
},
{
"to": [
"boltz_boltz2_affinity_predictor.msa_path"
],
"from": "inha_ligand_setup.msa_path"
},
{
"to": [
"boltz_boltz2_affinity_predictor.run_options"
],
"from": "inha_ligand_setup.run_options"
},
{
"to": [
"tb_prediction_interpreter.assembled_boltz_request",
"visualisation.inha_ligand_setup_assembled_boltz_request"
],
"from": "inha_ligand_setup.assembled_boltz_request"
},
{
"to": [
"visualisation.boltz_boltz2_affinity_predictor_affinity_summary",
"tb_prediction_interpreter.boltz_boltz2_affinity_predictor_affinity_summary"
],
"from": "boltz_boltz2_affinity_predictor.affinity_summary"
},
{
"to": [
"visualisation.boltz_boltz2_affinity_predictor_confidence_summary",
"tb_prediction_interpreter.boltz_boltz2_affinity_predictor_confidence_summary"
],
"from": "boltz_boltz2_affinity_predictor.confidence_summary"
},
{
"to": [
"visualisation.boltz_boltz2_affinity_predictor_structure_artifacts",
"tb_prediction_interpreter.boltz_boltz2_affinity_predictor_structure_artifacts"
],
"from": "boltz_boltz2_affinity_predictor.structure_artifacts"
},
{
"to": [
"visualisation.boltz_boltz2_affinity_predictor_run_metadata",
"tb_prediction_interpreter.boltz_boltz2_affinity_predictor_run_metadata"
],
"from": "boltz_boltz2_affinity_predictor.run_metadata"
},
{
"to": [
"visualisation.tb_prediction_interpreter_prediction_evidence"
],
"from": "tb_prediction_interpreter.prediction_evidence"
}
],
"runtime": {
"duration": 0.01,
"settle_steps": 1,
"initial_inputs": {},
"communication_step": 0.01
},
"description": "Guided Boltz-2 workflow for exploring a Mycobacterium tuberculosis InhA target with a triclosan reference ligand example, binder probability, affinity-like value, confidence metrics, and reproducible report context.",
"schema_version": "2.0"
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